基于GEO数据库糖尿病肾病患者基因芯片数据的生物信息学分析  

Bioinformatics analysis of gene chip data of diabetic nephropathy patients based on GEO database

作　　者：丁淑涵 张法荣[2] DING Shuhan

机构地区：[1]山东中医药大学,山东济南250000 [2]山东中医药大学附属医院,山东济南250000

出　　处：《中医临床研究》2023年第31期46-51,共6页Clinical Journal Of Chinese Medicine

摘　　要：目的:通过生物信息学的方法分析糖尿病肾病的肾小球组织与正常肾小球组织之间的差异基因,为进一步研究糖尿病肾病的发生、发展机制提供思路。方法:从基因表达数据库(Gene Expression Omnibus,GEO)下载芯片数据GSE96804,通过t检验获得差异基因。然后使用DAVID数据库对差异表达基因进行京都基因与基因组百科全书(KEGG)信号通路富集分析。结果:共获得差异基因76个,其中在糖尿病肾病肾小球组织中表达下调的基因有57个,表达上调的基因有19个。KEGG信号通路富集分析主要包括了丝裂原活化蛋白激酶(Mitogen-Activated Protein Kinase,MAPK)信号通路、内吞作用通路、雌激素信号通路、氧化磷酸化通路、内质网中的蛋白质加工通路、抗原处理和呈递通路。蛋白质-蛋白质相互作用分析筛选获得了关键基因13个,分别为FOS原癌基因(Fos Proto-Oncogene,FOS),双特异性磷酸酶1(Dual Specificity Phosphatase 1,DUSP1),热休克蛋白家族A(Hsp70)成员1A[Heat Shock Protein Family A(Hsp70)Member 1A,HSPA1A],辅酶A合成酶(Coenzyme A Synthase,COASY)等,其中有12个下调基因(FOS,DUSP1,HSPA1A等),一个上调基因[Dicer1,RNA酶Ⅲ(Dicer 1,Ribonuclease III,DICER1)]。结论:糖尿病肾病肾小球组织与正常肾小球组织基因表达存在差异的关键基因多与信息转导和能量代谢相关,采用生物信息学方法筛选出的核心靶点有利于从基因层面进一步了解糖尿病肾病的发生机制。Objective:To analyze the differentially expressed genes between glomerular tissue of diabetic nephropathy and normal glomerular tissue by bioinformatics method,so as to provide ideas for further study on the occurrence or development mechanism of diabetic nephropathy.Methods:The microarray data GSE96804 was downloaded from Gene Expression Omnibus(GEO),and the differentially expressed genes were obtained by t test.Then,the DAVID database was used to analyze the signal pathway enrichment of the differentially expressed genes in the Kyoto Encyclopedia of Genes and Genomes(KEGG).Results:A total of 76 differentially expressed genes were obtained,including 57 down regulated genes and 19 up-regulated genes.Enrichment analysis of KEGG signaling pathway mainly includes MAPK signaling pathway,endocytosis pathway,estrogen signaling pathway,etc..A total of 13 key genes were identified by proteinprotein interaction(PPI)analysis,including FOS,DUSP1,HSPA1A,etc.,and 12 down regulated genes(FOS,DUSP1,HSPA1A,etc.),and one up-regulated gene(DICER1).Conclusion:The key genes of gene expression difference between diabetic nephropathy glomerular tissue and normal glomerular tissue are mostly related to information transduction and energy metabolism.The core target screened by bioinformatics method is helpful to further understand the pathogenesis of diabetic nephropathy from the gene level.

关 键 词：糖尿病肾病 基因表达数据库 计算生物学 生物信息学分析 基因芯片 

分 类 号：R587.1[医药卫生—内分泌]